Low power and Lossy Networks (LLNs), e.g., sensor networks, have a myriad of applications, such as Smart Grid and Smart Cities. Various challenges are presented with LLNs, such as lossy links, low bandwidth, battery operation, low memory and/or processing capability, etc. One example routing solution to LLN challenges is a protocol called Routing Protocol for LLNs or “RPL,” which is a distance vector routing protocol that builds a Destination Oriented Directed Acyclic Graph (DODAG) in addition to a set of features to bound control traffic, support local (and slow) repair, etc. The RPL routing protocol provides a flexible method by which each node performs DODAG discovery, construction, and maintenance.
One problem that confronts LLNs is network stability, and as such, various measures to reduce management traffic have been established, such as limiting response to link failure and “smoothing” dynamic metric values so new metrics are only advertised when their values exceed some threshold. In particular, since electing a new parent in a DAG leads to unstable routing topologies, traffic flaps, jitter, etc., new metrics are advertised only if the metric values substantially change. The disadvantage of such an approach is the resulting cumulative effect (cumulative error), where for “deep” networks (networks having a large number of hops), the cumulative error could result in either a better unselected path being available or, conversely, a selected path that is worse than believed. Current solutions in RPL consist of rebuilding the entire DAG manually or upon the expiration of a timer, which can be costly, inefficient and not related to actual changes in the network.